{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# matplotlib绘制子图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "语法和MATLAB几乎相同"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAD8CAYAAAB6paOMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAFfJJREFUeJzt3X+s3XV9x/HnyyKQodO6dgkpHVRXB8wtgifIYjJdFKj80Zq4bGUhgmFrwsQluixh8Q+W8o+b2VxM2KDbGnXJKMofy12maYhASBbrehoYgy7otXPQzoSrRf7BwSjv/fH9snt66e359t7Te27v9/lITvr9fr7fz7nvfnLued3v71QVkqT+etO0C5AkTZdBIEk9ZxBIUs8ZBJLUcwaBJPWcQSBJPTc2CJLsTfJ8kqcWWZ4kX0oym+TJJFePLLslyffa1y2TLFySNBldtgi+DGw7zfKPAlvb1y7grwGSvAO4C3g/cA1wV5L1yylWkjR5Y4Ogqh4Djp9mlR3AV6txAHh7kouBG4CHqup4Vb0APMTpA0WSNAXnTeA9NgHPjcwfbdsWa3+DJLtotia46KKL3nf55ZdPoCxJ6o9Dhw79qKo2LqXvJIJg2apqD7AHYDAY1HA4nHJFknRuSfJfS+07ibOGjgGbR+YvadsWa5ckrSKTCIIZ4BPt2UPXAi9W1Q+B/cD1Sda3B4mvb9skSavI2F1DSe4HPgRsSHKU5kygNwNU1b3AN4AbgVngJeCT7bLjSe4GDrZvtbuqTnfQWZI0BWODoKpuGrO8gE8tsmwvsHdppUmSVoJXFktSzxkEktRzBoEk9ZxBIEk9ZxBIUs8ZBJLUcwaBJPWcQSBJPWcQSFLPGQSS1HMGgST1nEEgST1nEEhSzxkEktRzBoEk9ZxBIEk91ykIkmxL8kyS2SR3nmL5F5M80b6+m+QnI8tOjCybmWTxkqTl6/KoynXAPcB1wFHgYJKZqjr8+jpV9ZmR9T8NXDXyFj+tqvdOrmRJ0iR12SK4BpitqiNV9QqwD9hxmvVvAu6fRHGSpLOvSxBsAp4bmT/atr1BkkuBLcDDI80XJhkmOZDkY4v029WuM5ybm+tYuiRpEiZ9sHgn8GBVnRhpu7SqBsDvAH+Z5F0LO1XVnqoaVNVg48aNEy5JknQ6XYLgGLB5ZP6Stu1UdrJgt1BVHWv/PQI8ysnHDyRJU9YlCA4CW5NsSXI+zZf9G87+SXI5sB749kjb+iQXtNMbgA8Ahxf2lSRNz9izhqrq1SR3APuBdcDeqno6yW5gWFWvh8JOYF9V1Uj3K4D7krxGEzqfHz3bSJI0fTn5e3v6BoNBDYfDaZchSeeUJIfa47FnzCuLJannDAJJ6jmDQJJ6ziCQpJ4zCCSp5wwCSeo5g0CSes4gkKSeMwgkqecMAknqOYNAknrOIJCknjMIJKnnDAJJ6jmDQJJ6ziCQpJ7rFARJtiV5JslskjtPsfzWJHNJnmhfvzuy7JYk32tft0yyeEnS8o19VGWSdcA9wHXAUeBgkplTPHLygaq6Y0HfdwB3AQOggENt3xcmUr0kadm6bBFcA8xW1ZGqegXYB+zo+P43AA9V1fH2y/8hYNvSSpUknQ1dgmAT8NzI/NG2baGPJ3kyyYNJNp9J3yS7kgyTDOfm5jqWLkmahEkdLP4n4LKq+lWav/q/ciadq2pPVQ2qarBx48YJlSRJ6qJLEBwDNo/MX9K2/b+q+nFVvdzO/i3wvq59JUnT1SUIDgJbk2xJcj6wE5gZXSHJxSOz24H/aKf3A9cnWZ9kPXB92yZJWiXGnjVUVa8muYPmC3wdsLeqnk6yGxhW1QzwB0m2A68Cx4Fb277Hk9xNEyYAu6vq+Fn4f0iSlihVNe0aTjIYDGo4HE67DEk6pyQ5VFWDpfT1ymJJ6jmDQJJ6ziCQpJ4zCCSp5wwCSeo5g0CSes4gkKSeMwgkqecMAknqOYNAknrOIJCknjMIJKnnDAJJ6jmDQJJ6ziCQpJ7rFARJtiV5JslskjtPsfyzSQ63D6//VpJLR5adSPJE+5pZ2FeSNF1jn1CWZB1wD3AdcBQ4mGSmqg6PrPY4MKiql5LcDvwZ8Nvtsp9W1XsnXLckaUK6bBFcA8xW1ZGqegXYB+wYXaGqHqmql9rZAzQPqZcknQO6BMEm4LmR+aNt22JuA745Mn9hkmGSA0k+dqoOSXa16wzn5uY6lCRJmpSxu4bORJKbgQHwwZHmS6vqWJJ3Ag8n+feq+v5ov6raA+yB5pnFk6xJknR6XbYIjgGbR+YvadtOkuQjwOeA7VX18uvtVXWs/fcI8Chw1TLqlSRNWJcgOAhsTbIlyfnATuCks3+SXAXcRxMCz4+0r09yQTu9AfgAMHqQWZI0ZWN3DVXVq0nuAPYD64C9VfV0kt3AsKpmgC8AbwG+ngTg2araDlwB3JfkNZrQ+fyCs40kSVOWqtW1S34wGNRwOJx2GZJ0TklyqKoGS+nrlcWS1HMGgST1nEEgST1nEEhSzxkEktRzBoEk9ZxBIEk9ZxBIUs8ZBJLUcwaBJPWcQSBJPWcQSFLPGQSS1HMGgST1nEEgST1nEEhSz3UKgiTbkjyTZDbJnadYfkGSB9rl30ly2ciyP27bn0lyw+RKlyRNwtggSLIOuAf4KHAlcFOSKxesdhvwQlX9IvBF4E/bvlfSPOP4l4FtwF+17ydJWiW6bBFcA8xW1ZGqegXYB+xYsM4O4Cvt9IPAh9M8vHgHsK+qXq6q/wRm2/eTJK0SYx9eD2wCnhuZPwq8f7F12ofdvwj8XNt+YEHfTQt/QJJdwK529uUkT3Wqfu3bAPxo2kWsEo7FPMdinmMx75eW2rFLEJx1VbUH2AOQZLjUBzCvNY7FPMdinmMxz7GYl2S41L5ddg0dAzaPzF/Stp1ynSTnAW8DftyxryRpiroEwUFga5ItSc6nOfg7s2CdGeCWdvo3gYerqtr2ne1ZRVuArcC/TqZ0SdIkjN011O7zvwPYD6wD9lbV00l2A8OqmgH+Dvj7JLPAcZqwoF3va8Bh4FXgU1V1YsyP3LP0/86a41jMcyzmORbzHIt5Sx6LNH+4S5L6yiuLJannDAJJ6rmpBcFyblux1nQYi88mOZzkySTfSnLpNOpcCePGYmS9jyepJGv21MEuY5Hkt9rPxtNJ/mGla1wpHX5HfiHJI0keb39PbpxGnWdbkr1Jnl/sWqs0vtSO05NJru70xlW14i+ag87fB94JnA/8G3DlgnV+H7i3nd4JPDCNWlfJWPwG8DPt9O19Hot2vbcCj9FcrDiYdt1T/FxsBR4H1rfzPz/tuqc4FnuA29vpK4EfTLvuszQWvw5cDTy1yPIbgW8CAa4FvtPlfae1RbCc21asNWPHoqoeqaqX2tkDNNdjrEVdPhcAd9Pcz+p/VrK4FdZlLH4PuKeqXgCoqudXuMaV0mUsCvjZdvptwH+vYH0rpqoeozkzczE7gK9W4wDw9iQXj3vfaQXBqW5bsfDWEyfdtgJ4/bYVa02XsRh1G03ir0Vjx6Ld1N1cVf+8koVNQZfPxbuBdyf5lyQHkmxbsepWVpex+BPg5iRHgW8An16Z0ladM/0+AVbJLSbUTZKbgQHwwWnXMg1J3gT8BXDrlEtZLc6j2T30IZqtxMeS/EpV/WSqVU3HTcCXq+rPk/wazXVN76mq16Zd2LlgWlsEy7ltxVrT6TYcST4CfA7YXlUvr1BtK23cWLwVeA/waJIf0OwDnVmjB4y7fC6OAjNV9b/V3N33uzTBsNZ0GYvbgK8BVNW3gQtpbkjXN0u6rc+0gmA5t61Ya8aORZKrgPtoQmCt7geGMWNRVS9W1YaquqyqLqM5XrK9qpZ8s61VrMvvyD/SbA2QZAPNrqIjK1nkCukyFs8CHwZIcgVNEMytaJWrwwzwifbsoWuBF6vqh+M6TWXXUC3jthVrTcex+ALwFuDr7fHyZ6tq+9SKPks6jkUvdByL/cD1SQ4DJ4A/qqo1t9XccSz+EPibJJ+hOXB861r8wzHJ/TThv6E9HnIX8GaAqrqX5vjIjTTPfnkJ+GSn912DYyVJOgNdHlW55AsYktyS5Hvt65ZT9ZckTVeXYwRfpnne8GI+SnOAaivNU8b+GiDJO2g2W95Pcx7wXUnWL6dYSdLkjQ2CZVzAcAPwUFUdby94eYjTB4okaQomcbB4sQsYOl/YkJFnFl900UXvu/zyyydQliT1x6FDh35UVRuX0ndVXFBWI88sHgwGNRyuxbMBJensSfJfS+07iesIFruAwecVS9I5YBJBsNgFDK+f47y+PUh8fdsmSVpFxu4aWuoFDFV1PMndNFcFAuyuqtMddJYkTUGXh9ffNGZ5AZ9aZNleYO/SSpMkrQQfVSlJPWcQSFLPGQSS1HMGgST1nEEgST1nEEhSzxkEktRzBoEk9ZxBIEk9ZxBIUs8ZBJLUcwaBJPWcQSBJPWcQSFLPGQSS1HMGgST1XKcgSLItyTNJZpPceYrlX0zyRPv6bpKfjCw7MbJsZpLFS5KWr8ujKtcB9wDXAUeBg0lmqurw6+tU1WdG1v80cNXIW/y0qt47uZIlSZPUZYvgGmC2qo5U1SvAPmDHada/Cbh/EsVJks6+LkGwCXhuZP5o2/YGSS4FtgAPjzRfmGSY5ECSjy3Sb1e7znBubq5j6ZKkSZj0weKdwINVdWKk7dKqGgC/A/xlknct7FRVe6pqUFWDjRs3TrgkSdLpdAmCY8DmkflL2rZT2cmC3UJVdaz99wjwKCcfP5AkTVmXIDgIbE2yJcn5NF/2bzj7J8nlwHrg2yNt65Nc0E5vAD4AHF7YV5I0PWPPGqqqV5PcAewH1gF7q+rpJLuBYVW9Hgo7gX1VVSPdrwDuS/IaTeh8fvRsI0nS9OXk7+3pGwwGNRwOp12GJJ1Tkhxqj8eeMa8slqSeMwgkqecMAknqOYNAknrOIJCknjMIJKnnDAJJ6jmDQJJ6ziCQpJ4zCCSp5wwCSeo5g0CSes4gkKSeMwgkqecMAknquU5BkGRbkmeSzCa58xTLb00yl+SJ9vW7I8tuSfK99nXLJIuXJC3f2CeUJVkH3ANcBxwFDiaZOcWTxh6oqjsW9H0HcBcwAAo41PZ9YSLVS5KWrcsWwTXAbFUdqapXgH3Ajo7vfwPwUFUdb7/8HwK2La1USdLZ0CUINgHPjcwfbdsW+niSJ5M8mGTzmfRNsivJMMlwbm6uY+mSpEmY1MHifwIuq6pfpfmr/ytn0rmq9lTVoKoGGzdunFBJkqQuugTBMWDzyPwlbdv/q6ofV9XL7ezfAu/r2leSNF1dguAgsDXJliTnAzuBmdEVklw8Mrsd+I92ej9wfZL1SdYD17dtkqRVYuxZQ1X1apI7aL7A1wF7q+rpJLuBYVXNAH+QZDvwKnAcuLXtezzJ3TRhArC7qo6fhf+HJGmJUlXTruEkg8GghsPhtMuQpHNKkkNVNVhKX68slqSeMwgkqecMAknqOYNAknrOIJCknjMIJKnnDAJJ6jmDQJJ6ziCQpJ4zCCSp5wwCSeo5g0CSes4gkKSeMwgkqecMAknqOYNAknquUxAk2ZbkmSSzSe48xfLPJjmc5Mkk30py6ciyE0meaF8zC/tKkqZr7KMqk6wD7gGuA44CB5PMVNXhkdUeBwZV9VKS24E/A367XfbTqnrvhOuWJE1Ily2Ca4DZqjpSVa8A+4AdoytU1SNV9VI7ewC4ZLJlSpLOli5BsAl4bmT+aNu2mNuAb47MX5hkmORAko+dqkOSXe06w7m5uQ4lSZImZeyuoTOR5GZgAHxwpPnSqjqW5J3Aw0n+vaq+P9qvqvYAe6B5eP0ka5IknV6XLYJjwOaR+UvatpMk+QjwOWB7Vb38entVHWv/PQI8Cly1jHolSRPWJQgOAluTbElyPrATOOnsnyRXAffRhMDzI+3rk1zQTm8APgCMHmSWJE3Z2F1DVfVqkjuA/cA6YG9VPZ1kNzCsqhngC8BbgK8nAXi2qrYDVwD3JXmNJnQ+v+BsI0nSlKVqde2SHwwGNRwOp12GJJ1TkhyqqsFS+nplsST1nEEgST1nEEhSzxkEktRzBoEk9ZxBIEk9ZxBIUs8ZBJLUcwaBJPWcQSBJPWcQSFLPGQSS1HMGgST1nEEgST1nEEhSzxkEktRznYIgybYkzySZTXLnKZZfkOSBdvl3klw2suyP2/ZnktwwudIlSZMwNgiSrAPuAT4KXAnclOTKBavdBrxQVb8IfBH407bvlTTPOP5lYBvwV+37SZJWiS5bBNcAs1V1pKpeAfYBOxasswP4Sjv9IPDhNA8v3gHsq6qXq+o/gdn2/SRJq8TYh9cDm4DnRuaPAu9fbJ32YfcvAj/Xth9Y0HfTwh+QZBewq519OclTnapf+zYAP5p2EauEYzHPsZjnWMz7paV27BIEZ11V7QH2ACQZLvUBzGuNYzHPsZjnWMxzLOYlGS61b5ddQ8eAzSPzl7Rtp1wnyXnA24Afd+wrSZqiLkFwENiaZEuS82kO/s4sWGcGuKWd/k3g4aqqtn1ne1bRFmAr8K+TKV2SNAljdw21+/zvAPYD64C9VfV0kt3AsKpmgL8D/j7JLHCcJixo1/sacBh4FfhUVZ0Y8yP3LP2/s+Y4FvMci3mOxTzHYt6SxyLNH+6SpL7yymJJ6jmDQJJ6bmpBsJzbVqw1Hcbis0kOJ3kyybeSXDqNOlfCuLEYWe/jSSrJmj11sMtYJPmt9rPxdJJ/WOkaV0qH35FfSPJIksfb35Mbp1Hn2ZZkb5LnF7vWKo0vteP0ZJKrO71xVa34i+ag8/eBdwLnA/8GXLlgnd8H7m2ndwIPTKPWVTIWvwH8TDt9e5/Hol3vrcBjNBcrDqZd9xQ/F1uBx4H17fzPT7vuKY7FHuD2dvpK4AfTrvssjcWvA1cDTy2y/Ebgm0CAa4HvdHnfaW0RLOe2FWvN2LGoqkeq6qV29gDN9RhrUZfPBcDdNPez+p+VLG6FdRmL3wPuqaoXAKrq+RWucaV0GYsCfradfhvw3ytY34qpqsdozsxczA7gq9U4ALw9ycXj3ndaQXCq21YsvPXESbetAF6/bcVa02UsRt1Gk/hr0dixaDd1N1fVP69kYVPQ5XPxbuDdSf4lyYEk21asupXVZSz+BLg5yVHgG8CnV6a0VedMv0+AVXKLCXWT5GZgAHxw2rVMQ5I3AX8B3DrlUlaL82h2D32IZivxsSS/UlU/mWpV03ET8OWq+vMkv0ZzXdN7quq1aRd2LpjWFsFyblux1nS6DUeSjwCfA7ZX1csrVNtKGzcWbwXeAzya5Ac0+0Bn1ugB4y6fi6PATFX9bzV39/0uTTCsNV3G4jbgawBV9W3gQpob0vXNkm7rM60gWM5tK9aasWOR5CrgPpoQWKv7gWHMWFTVi1W1oaouq6rLaI6XbK+qJd9saxXr8jvyjzRbAyTZQLOr6MhKFrlCuozFs8CHAZJcQRMEcyta5eowA3yiPXvoWuDFqvrhuE5T2TVUy7htxVrTcSy+ALwF+Hp7vPzZqto+taLPko5j0Qsdx2I/cH2Sw8AJ4I+qas1tNXcciz8E/ibJZ2gOHN+6Fv9wTHI/TfhvaI+H3AW8GaCq7qU5PnIjzbNfXgI+2el91+BYSZLOgFcWS1LPGQSS1HMGgST1nEEgST1nEEhSzxkEktRzBoEk9dz/AW/TZwi3ZM4HAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(2, 1, 1)    # 2 X  1\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(1, 2, 1)    # 2 X  1\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(2, 2, 1)\n",
    "plt.subplot(2, 2, 2)\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.show() \n",
    "# 先看成2*2的，然后到下面时看成2*1的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "plt.subplot(2, 2, 1)\n",
    "x = np.random.random(10)\n",
    "y = np.random.random(10)\n",
    "plt.scatter(x, y)\n",
    "plt.title('test')\n",
    "\n",
    "plt.subplot(2, 2, 2)\n",
    "x = np.arange(7)\n",
    "y = x**2\n",
    "plt.plot(x, y)\n",
    "\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.show() \n",
    "# 先看成2*2的，然后到下面时看成2*1的"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
